Producing frequency-modulated sonar systems for commercial applications such as fish finding routinely faces cost pressures. Thus, advanced signal processing techniques must be implemented in an efficient, cost-effective manner. For example, it is desirable to offer relatively high power, such as 1 kW over a wideband frequency range, such as 25 kHz to 255 kHz. The lower frequencies are desirable for deep water operation whereas the higher frequencies offer better resolution in shallow water operation.
The received signal power varies greatly depending upon what depth of operation for a sonar system. The reflected sonar pulse is relatively strong from shallow targets. In contrast, the reflected sonar pulse is relatively weak from deeper targets due to the greater ranges that the deep water reflected pulse must travel. Thus, a sonar receiver capable of operating in both shallow and deep water must accommodate a wide dynamic range in received pulse power such as 120 dB.
An analog-to-digital converter (ADC) requires 20 bits of resolution to directly capture such a large dynamic range. In that regard, 20 bits of resolution means that the ADC is capable of distinguishing over one million different amplitude levels. Such a high-resolution ADC is costly and thus inappropriate for commercial operation.
The receiver costs are exacerbated for a wideband sonar system. But wideband operation is desirable in that pulse compression techniques such as a chirp pulse provide enhanced range resolution. In that regard, range resolution in sonar systems is a function of the effective pulse length. The shorter the effective pulse, the greater the range resolution. But sonar performance is also dependent upon the achievable signal-to-noise ratio (SNR) for the received sonar pulses. In general, the greater the energy for the transmitted pulses, the greater the SNR is for the resulting received pulses. Achieving higher SNR and shorter pulse lengths are thus at odds with one another—for a sonar system with a given transmit power, the SNR is reduced as the pulse length is reduced. Pulse compression techniques enable sonar systems to achieve finer range resolution without sacrificing SNR. To achieve this goal, the pulses may be frequency modulated across a relatively long pulse extent or length. For example, FIG. 1 shows the time domain signal for a received frequency-modulated pulse 100. If the frequency modulation is linear as shown in FIG. 1, pulse 100 is commonly denoted as a chirp pulse. However, non-linear frequency modulation or phase modulation may also be used to achieve pulse compression.
In a pulse compression sonar system, the sonar receiver correlates a replica pulse 105 with the received pulse 100. The resulting detection peak 110 is much narrower than the original pulse length, thus representing the pulse compression effect. In a chirp embodiment, the effective compressed pulse length T′ (as defined by the 3 dB width for detection peak 110) equals 1/Δf, where Δf is the frequency difference modulated across pulse 100. So the effective pulse is narrowed but the SNR still corresponds to the original pulse width. Thus pulse compression methods are a popular technique to achieve greater range resolution.
Pulse 100 is unshaped in that it has a constant amplitude across all the frequencies. The correlation of an unshaped pulse with its replica in the sonar receiver produces relatively high amplitude range sidelobes as shown in FIG. 1. To reduce these range sidelobes, it is common to amplitude shape the pulses such as seen for a transmitted pulse 200 and a corresponding replica pulse 205 in FIG. 2. The resulting range sidelobes are lowered as compared to the unshaped case of FIG. 1 but the shaping results in lower transmitted pulse power and thus a lower SNR for the received pulses. Moreover, the reduction in range sidelobes demands a high degree of fidelity between the transmitted signal and the stored replica. The signal distortion due to propagation and reflection thus prohibits a significant improvement in sidelobe levels.
Achieving efficient pulse compression yet also having good SNR is not the only challenge for sonar systems. For example, fish-finding sonar systems must fight a variety of interferences such as background noise or signals from other sonar systems. These interferences complicate the task of distinguishing bottom echoes and mask the desired fish detection. To address interferences such as clutter due to water quality, suspended particles such as zooplankton, and thermocline detection, a standard processing scheme employs time averaging of the detected signal. However, time averaging often has very limited effectiveness against these problems.
Accordingly, there is a need in the art for improved sonar systems that offer frequency agile performance and relatively high power at low cost. In addition, there is a need in the art for improved sonar systems that offer pulse compression and sidelobe suppression at low cost. Finally, there is a need in the art for improved sonar processing techniques.